8,434 research outputs found
Electroweak Chiral Lagrangian for a Hypercharge-universal Topcolor Model
Electroweak chiral Lagrangian for a hypercharge-universal topcolor model is
investigated. We find that the assignments of universal hypercharge improve the
results obtained previously from K.Lane's prototype natural TC2 model by
allowing a larger Z' mass resulting in a very small T parameter and the S
parameter is still around the order of +1Comment: 12 pages, 7 figure
Dynamical Computation on Coefficients of Electroweak Chiral Lagrangian from One-doublet and Topcolor-assisted Technicolor Models
Based on previous studies deriving the chiral Lagrangian for pseudo scalar
mesons from the first principle of QCD, we derive the electroweak chiral
Lagrangian and build up a formulation for computing its coefficients from
one-doublet technicolor model and a schematic topcolor-assisted technicolor
model. We find that the coefficients of the electroweak chiral Lagrangian for
the topcolor-assisted technicolor model are divided into three parts: direct
TC2 interaction part, TC1 and TC2 induced effective Z' particle contribution
part, and ordinary quarks contribution part. The first two parts are computed
in this paper and we show that the direct TC2 interaction part is the same as
that in the one-doublet technicolor model, while effective Z' contributions are
at least proportional to the p^2 order parameter \beta_1 in the electroweak
chiral Lagrangian and typical features of topcolor-assisted technicolor model
are that it only allows positive T and U parameters and the T parameter varies
in the range 0\sim 1/(25\alpha), the upper bound of T parameter will decrease
as long as Z' mass become large. The S parameter can be either positive or
negative depending on whether the Z' mass is large or small. The Z' mass is
also bounded above and the upper bound depend on value of T parameter. We
obtain the values for all the coefficients of the electroweak chiral Lagrangian
up to order of p^4.Comment: 52 pages, 15 figure
Single chargino production via gluon-gluon fusion in a supersymmetric theory with an explicit R-parity violation
We studied the production of single chargino
accompanied by lepton via gluon-gluon fusion at the LHC. The
numerical analysis of their production rates is carried out in the mSUGRA
scenario with some typical parameter sets. The results show that the cross
sections of the productions via gluon-gluon
collision are in the order of femto barn quantitatively at the
CERN LHC, and can be competitive with production mechanism via quark-antiquark
annihilation process.Comment: LaTex file, 18 pages, 4 EPS file
Diving Deep into Sentiment: Understanding Fine-tuned CNNs for Visual Sentiment Prediction
Visual media are powerful means of expressing emotions and sentiments. The
constant generation of new content in social networks highlights the need of
automated visual sentiment analysis tools. While Convolutional Neural Networks
(CNNs) have established a new state-of-the-art in several vision problems,
their application to the task of sentiment analysis is mostly unexplored and
there are few studies regarding how to design CNNs for this purpose. In this
work, we study the suitability of fine-tuning a CNN for visual sentiment
prediction as well as explore performance boosting techniques within this deep
learning setting. Finally, we provide a deep-dive analysis into a benchmark,
state-of-the-art network architecture to gain insight about how to design
patterns for CNNs on the task of visual sentiment prediction.Comment: Preprint of the paper accepted at the 1st Workshop on Affect and
Sentiment in Multimedia (ASM), in ACM MultiMedia 2015. Brisbane, Australi
Threshold for the Outbreak of Cascading Failures in Degree-degree Uncorrelated Networks
In complex networks, the failure of one or very few nodes may cause cascading
failures. When this dynamical process stops in steady state, the size of the
giant component formed by remaining un-failed nodes can be used to measure the
severity of cascading failures, which is critically important for estimating
the robustness of networks. In this paper, we provide a cascade of overload
failure model with local load sharing mechanism, and then explore the threshold
of node capacity when the large-scale cascading failures happen and un-failed
nodes in steady state cannot connect to each other to form a large connected
sub-network. We get the theoretical derivation of this threshold in
degree-degree uncorrelated networks, and validate the effectiveness of this
method in simulation. This threshold provide us a guidance to improve the
network robustness under the premise of limited capacity resource when creating
a network and assigning load. Therefore, this threshold is useful and important
to analyze the robustness of networks.Comment: 11 pages, 4 figure
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